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Abstract:
The purpose of this study is to evaluate the eight ISIMIP2a biome models against independent
estimates of long-term net carbon fluxes (i.e. Net Biome Productivity, NBP) over terrestrial
ecosystems for the recent four decades (1971–2010). We evaluate modeled global NBP against 1)
the updated global residual land sink (RLS) plus land use emissions (ELUC) from the Global
Carbon Project (GCP), presented as R þ L in this study by Le Quéré et al (2015), and 2) the
land CO2 fluxes from two atmospheric inversion systems: Jena CarboScope s81_v3.8 and CAMS
v15r2, referred to as FJena and FCAMS respectively. The model ensemble-mean NBP (that includes
seven models with land-use change) is higher than but within the uncertainty of R þ L, while
the simulated positive NBP trend over the last 30 yr is lower than that from R þ L and from the
two inversion systems. ISIMIP2a biome models well capture the interannual variation of global
net terrestrial ecosystem carbon fluxes. Tropical NBP represents 31 ± 17% of global total NBP
during the past decades, and the year-to-year variation of tropical NBP contributes most of the
interannual variation of global NBP. According to the models, increasing Net Primary
Productivity (NPP) was the main cause for the generally increasing NBP. Significant global NBP
anomalies from the long-term mean between the two phases of El Niño Southern Oscillation
(ENSO) events are simulated by all models (p < 0.05), which is consistent with the R þ L
estimate (p ¼ 0.06), also mainly attributed to NPP anomalies, rather than to changes in
heterotrophic respiration (Rh). The global NPP and NBP anomalies during ENSO events are
dominated by their anomalies in tropical regions impacted by tropical climate variability.
Multiple regressions between R þ L, FJena and FCAMS interannual variations and tropical climate variations reveal a significant negative response of global net terrestrial ecosystem carbon fluxes
to tropical mean annual temperature variation, and a non-significant response to tropical annual
precipitation variation. According to the models, tropical precipitation is a more important
driver, suggesting that some models do not capture the roles of precipitation and temperature changes adequately.
